缺失值混合数据聚类的插值策略

IF 1.8 4区 计算机科学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Rabea Aschenbruck, G. Szepannek, A. Wilhelm
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引用次数: 2

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。

Imputation Strategies for Clustering Mixed-Type Data with Missing Values

Imputation Strategies for Clustering Mixed-Type Data with Missing Values
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来源期刊
Journal of Classification
Journal of Classification 数学-数学跨学科应用
CiteScore
3.60
自引率
5.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: To publish original and valuable papers in the field of classification, numerical taxonomy, multidimensional scaling and other ordination techniques, clustering, tree structures and other network models (with somewhat less emphasis on principal components analysis, factor analysis, and discriminant analysis), as well as associated models and algorithms for fitting them. Articles will support advances in methodology while demonstrating compelling substantive applications. Comprehensive review articles are also acceptable. Contributions will represent disciplines such as statistics, psychology, biology, information retrieval, anthropology, archeology, astronomy, business, chemistry, computer science, economics, engineering, geography, geology, linguistics, marketing, mathematics, medicine, political science, psychiatry, sociology, and soil science.
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